Predicted impact of banning nonessential, energy-dense food and beverages in schools in Mexico: A microsimulation study

Background Childhood obesity is a growing concern worldwide. School-based interventions have been proposed as effective means to improve nutritional knowledge and prevent obesity. In 2023, Mexico approved a reform to the General Education Law to strengthen the ban of sales and advertising of nonessential energy-dense food and beverages (NEDFBs) in schools and surroundings. We aimed to predict the expected one-year change in total caloric intake and obesity prevalence by introducing the ban of NEDFBs sales in schools, among school-aged children and adolescents (6 to 17 years old) in Mexico. Methods and findings We used age-specific equations to predict baseline fat-free mass (FFM) and fat mass (FM) and then estimated total energy intake (TEI) per day. The TEI after the intervention was estimated under 4 scenarios: (1) using national data to inform the intervention effect; (2) varying law compliance; (3) using meta-analytic data to inform the intervention effect size on calories; and (4) using national data to inform the intervention effect by sex and socioeconomic status (SES). We used Hall’s microsimulation model to estimate the potential impact on body weight and obesity prevalence of children and adolescents 1 year after implementing the intervention in Mexican schools. We found that children could reduce their daily energy intake by 33 kcal/day/person (uncertainty interval, UI, [25, 42] kcal/day/person), reducing on average 0.8 kg/person (UI [0.6, 1.0] kg/person) and 1.5 percentage points (pp) in obesity (UI [1.1, 1.9] pp) 1 year after implementing the law. We showed that compliance will be key to the success of this intervention: considering a 50% compliance the intervention effect could reduce 0.4 kg/person (UI [0.3, 0.5] kg/person). Our sensitivity analysis showed that the ban could reduce body weight by 1.3 kg/person (UI [0.8, 1.8] kg/person) and up to 5.4 kg/person (UI [3.4, 7.5] kg/person) in the best-case scenario. Study limitations include assuming that obesity and the contribution of NEDFBs consumed at school remain constant over time, assuming full compliance, and not considering the potential effect of banning NEDFBs in stores near schools. Conclusions Even in the most conservative scenario, banning sales of NEDFBs in schools is expected to significantly reduce obesity, but achieving high compliance will be key to its success. Why was this study done? - School-based interventions have been recognized as effective means to improve nutritional knowledge and prevent obesity-related diseases. - In December 2023, the Chamber of Representatives of Mexico approved an amendment that strengthens and updates the General Education Law (Article 75) and nutritional guidelines to ban the sales and advertising of nonessential energy-dense food and beverages (NEDFBs) in schools. What did the researchers do and find? - We used age-specific equations to predict baseline fat-free mass (FFM) and fat mass (FM) and total energy intake (TEI) per day. - We used microsimulation modeling to predict body weight and obesity prevalence of children and adolescents 1 year after implementing the intervention in Mexican schools. - Our modeling study suggests that an important impact on obesity prevalence can be expected if the law is implemented and enforced as intended. What do these findings mean? - If successful, this law could serve as an example beyond Mexico on how to achieve changes in body weight through school food regulation. - An important limitation of our main scenario is that we assumed full compliance of schools with the law, yet lower compliance will reduce its impact. We also did not consider historical trends on obesity or NEDFBs consumed in schools during our 1 year simulation, and we considered only the ban impact inside schools, excluding effects near and outside schools.

1 Nutritional criteria to determine banned foods and beverages in schools

2014 guidelines
Nutritional criteria considered to determine foods and beverages prohibited within Mexican schools published in "the general guidelines for the sale and distribution of prepared and processed foods and beverages in schools of the National Educational System" in 2014.*General guidelines for the sale and distribution of prepared and processed foods and beverages in schools of the National Educational System issued in 2014.
• Only secondary and high school are considered for the consumption of sugar-sweetened beverages.In elementary school, the exclusive consumption of water was promoted and the promotion of the consumption of other types of drinks was avoided.§ Processed foods that met the nutritional criteria could be consumed once a week (Friday).‡ Only if it contain added -fat, -salt or -sugars.

2023 guidelines
Nutritional criteria that will be considered in the 2023 reform of the General Education Law, based on the Official Mexican Standard (NOM-051-SCFI/SSA1-2010), "General labeling specifications for prepackaged foods and non-alcoholic beverages -Commercial information and Sanitation), of 2010 to determine foods and drinks that will be prohibited in schools.≥ 45 mg *Applied to prepackaged food or beverage with added specified nutrient, those products to which the specified nutrient has been added during the manufacturing process, and added ingredients that contain the specified nutrient.‡ Monosaccharides and disaccharides added to foods and non-alcoholic beverages by the manufacturer.

Data sources
We used anthropometric data of individuals aged 6-18 years old from the Mexican Health and Nutrition Survey (ENSANUT, from its Spanish acronym) 2018.Individuals aged 6-17 were taken as the baseline sample (initial sample) for simulation.Individuals aged 18 years old were considered only to obtain medians of fat mass and fat-free mass (Table F) needed to calibrate the model (calibration is presented in section 3).More details about the anthropometric data are presented in the next subsection.

Compliance rate
At least 30% Hugues et al. [11] a Used when considering caloric compensation, which was estimated separately for foods and beverages by Tallie et al. [8] b SES = Socioeconomic status 3 Total energy intake by day and calibration We estimated the daily total energy intake at baseline for each individual in the sample as [10]: where Parameters in Katan's equation are presented in Table D.

Energy expenditure of reference
We estimated the energy expenditure of reference in equation ( 1) as [10] where K represents an energy expenditure constant dependent on the child's sex (K = 800 kcal/d for males; K = 700 kcal/d for females); γ F = 4.5 kcal/kg/d and γ F F M = 22.4 kcal/kg/d are regression coefficients explaining the relationship between the resting metabolic rate (dependant variable), and F and F F M , respectively [14]. where The function for physical activity (δ) in equation ( 3) is given by: The minimum physical activity for all ages and sexes is represented by the constant δ min =10 kcal/kg/d.The constant for maximum physical activity is sex specific and given by δ max = 19 kcal/kg/d for males and δ max = 17 kcal/kg/d for females.The parameter P = 12 years represents the point of maximum physical activity whilst the constant h = 10 represents the rate of decline as a function of age.
The term g(t) in equation ( 3) controls children's body growth, estimated with the equation [10,13] where the specific parameters for males and females are shown in Table E.
where BM I and BW stand for body mass index and body weight, respectively.

Intervention scenarios
To estimate the reduction in caloric intake we constructed three scenarios: 1) using Mexican data to inform the intervention effect, 2) using Mexican data to inform the intervention effect varying compliance, and 3) using meta-analytic data to inform the intervention scenario, and 4) using national data to inform the intervention effect by sex and socioeconomic status.

Using Mexican data to inform the intervention effect
For the main scenario and scenario 4 (sensitivity analysis), we identified non-essential energy-dense food and beverages (NEDFBs) based on the established guidelines in Mexico in 2020 for labeling processed foods and beverages with "excess of" calories, added sugars, fats, trans fat, or sodium.[16].These guidelines are presented in Table G.For the main analysis, we estimated the consumption of NEDFBs inside schools stratified by type of school: elementary, junior high, and high school.For the sensitivity analysis 3, we stratified the NEDFBs inside school by sex and socioeconomic status.
Table G: General labeling specifications for prepackaged food and non-alcoholic beverages-Commercial and health information.

Supplemental nutritional
For solid foods per 100 grams: > 275 kcal total, information should be > 10% of the total energy from free sugars, included on the label of > 10% of the total energy from saturated fats, prepackaged product that: > 1% of the total from trans fat; for a) contain additives: free sodium> 350 mg/100g.sugars, fats or sodium.
For liquids for every 100 milliliters:> 70 kcal total or b) the energy value, the >10 kcal of free sugars, > 10% of the total energy amount of free sugars, from free sugars, > 10% of the total energy from saturated fat, trans fat and saturated fats, > 1% of the total from trans fat; sodium meet with the for sodium> 45 mg (non-calorie drinks).established nutritional profiles.

Definition of prepackaged
Prepackaged product with added free sugars are those in which free sugars have been added during the manufacturing process, and ingredients that contain added free sugars.Added prepackaged products of fats are those in which vegetable or animal fats, partially hydrogenated vegetable oils or products and ingredients containing them have been added during the manufacturing process.Added prepackaged sodium product are those in which any salt containing sodium or any ingredient containing added sodium has been used as an ingredient or additive during the manufacturing process.

Using Mexican data to the inform intervention effect, varying compliance
As a sensitivity analysis, we estimated the effect of compliance rate over the main scenarios (with and without energy compensation).As,the Food Frequency Questionnaire from ENSANUT 2018 does not include informa-tion to distinguish school consumption in Mexico, we assumed that the compliance rate would directly affect the change in body weight: Weight reduction compliance ≈ %compliance × Weight reduction main .
For example, in the main scenario without energy compensation, we estimated an average weight reduction of 2.3 kg (see Table 1 in the main manuscript).That reduction was estimated assuming a compliance rate of 100%.Thus, under 80% of compliance, the expected weight would be estimated as 80% × 2.3 kg = 1.8 kg.
To estimate reductions in obesity, we applied equation ( 9) for each individual in the sample and re-estimated obesity prevalence.

Using meta-analytic data to inform the intervention effect
This scenario is based on the meta-analysis performed by Micha et.al, evaluating interventions in the school food-environment.[17] We reviewed all the studies included in Micha's analysis and selected those that evaluated an intervention similar to ours (n =6), [18] ie, interventions that banned certain type of food and beverages.
Table H shows the studies included in our analysis.Since the meta-analysis included the period March 2014 to December 2017, we performed a rapid review with the same search terms as Micha, et al., ("Effectiveness of school food environment policies on children's dietary behaviors: A systematic review and meta-analysis") from December 2017 until 2022, and we identified another study published in 2020 estimating kcal reduction after modifying the nutrition standards and banning processed foods and beverages inside the school.[19] Using a random-effect model, we obtained a total reduction in energy intake of 177.0 kcal (95% CI [-241.9,-112.2])(Pooled in Table H).Given the heterogeneity of total energy intakes, we estimated the relative reduction from the pooled TEI of the control groups (1,811.0kcal) -before the intervention or unexposed to the intervention.This reduction represented a change of -9.8% (95% CI [-13.4%, -6.2%]) from TEI.The studies were observational without a control group, so there is likely an overestimation of the effect, especially when compared to Ensanut estimates.Hence, we consider three effects: 100% (point estimate), 50%, and 25% of the effect.

Microsimulation model
Body weight was simulated for each child or adolescent j in the data using the following equation: [10] BW j (t 365 ) = BW model j age j + t 365 ; sex j , F F M (t 0 ), F M (t 0 ), TEI (t 0 , t 365 ) (10) where t 0 = 0 is the initial time (year = 2018), t 365 = 365 (days; one year of simulation).F F M (t 0 ) and F M (t 0 ) are the initial (baseline) fat-free mass and fat mass of the child or adolescent, respectively, estimated with the Deurenberg formula (equations ( 7) and ( 8)).TEI (t 0 , t 365 ) is a vector containing daily energy intake from the initial time t 0 = 0 to the day t 365 = 365, and depends on the scenarios considered in the analyses.For the business-as-usual scenario, I ref (0) and I ref (d) are the energy intake of reference at the inital time and at day d, respectively, as estimated in section 3.For the intervention scenarios, we estimated the daily intake at day d considering the corresponding reduction: where % intake change = (1 − % reduction) for the main scenario without compensation and the sensitivity using a meta-analytic parameter, and % intake change = % compensation × (1 − % reduction) for the main scenarios with compensation.

Summary of Hall et al. equations
From Hall et al. [10], we know that: • EB(t) = I(t) + E(t); For our analysis, we assumed no trend in energy intake (∆I = 0).Then, we estimated the energy intake of reference (no intervention) as

Model validation
The original body weight model was calibrated using the reference body composition data from Mexican children presented in section 3.2.1.As a form of validation, we compared simulated average body weights of children aged 6-17, with observed average body weights of children 7-18 from the ENSANUT 2018 (Figures B and C).The simulated body weights were obtained from one year of simulation without intervention; we excluded individuals who changed their baseline BMI category.Our one-year predictions were consistent with the observed average weights by nutritional status for the corresponding ages in the ENSANUT survey, with average errors of 2.23 kg in underweight status, 0.56 kg in normal weight status, 1.22 kg in overweight status, 1.32 kg in obesity status and an overall error of 0.83 kg.

Uncertainty intervals
We estimated uncertainty intervals by generating 1,000 Monte Carlo simulations of the results, assuming normal distributions for the parameters considered in each scenario.For the scenario with and without energy compensation, we varied the % TEI from non-essential energy dense foods and beverages consumed at schools.For the scenario with energy compensation, we also varied the percentage of energy compensation by generating the change in regulated foods, change in non-regulated foods, change in regulated beverages, and change in non-regulated beverages.For the sensitivity using meta-analytical data, we simulated the uncertainty for the meta-analytical parameter, which represented the reduction in TEI estimated due to the ban.For the sensitivity analysis considering the ban effect by sex and socioeconomic status (SES), we varied the % TEI from non-essential energy-dense foods and beverages consumed at schools.The parameters described above were summarized in Table C. Uncertainty from the DCGO model, proposed by Hall et al., was not assessed due to computational time but in future projects, it could be done by simulating some model parameters.

Data available online
The database and a description of the variables considered for the analyses are available here (data.dta).All results were estimated considering the survey design (syntax in R with survey package [20][21][22] ): Svy .d e s i g n . 2 0 1 8 <− s v y d e s i g n ( i d = ˜1 , s t r a t a = ˜e s t d i s , PSU = ˜upm dis , w e i g h t s = ˜s v y w e i g h t s , data = data ) o p t i o n s ( s u r v e y .l o n e l y .psu = ' ' a d j u s t ' ' ) The database consists of children between 6 to 18 years old considered for estimating the median reference fat mass and fat-free mass presented in Table F (n = 10, 412).Those median values were estimated using the estimated baseline fat mass and fat-free mass (variables: initial fm, and initial ffm), and a rounded age in years (age years := round(age months/12)).Age in months (age months) was not used for the median estimations because of the lack of sample in some groups of age, sex and bmi categories.However, age in months (age months) was used for estimating body weight with Hall's model, and also Zscores for bmi and height.To replicate the main results using the database, set flag main results = 1 (n = 9,754, children between 6-17 years old).The file "Total energy intake by day.csv" includes the vector of total energy intake estimated for each children in "data.dta"(rows = individuals, columns = TEI by day).

Figure A :
Figure A: Data processing et al.[10] ref represents the reference energy intake: the required energy intake for children's normal growth, under no intervention.E ref corresponds to the reference energy expenditure, and EB ref denotes the energy balance of reference (= I ref − E ref ).Equations used for estimating EB ref and E ref are presented in the next subsections.To estimate E ref , average (or median) fat mass and fat-free mass values are needed; we considered median fat mass and fat-free mass by age, sex, and BMI category (calibration).Fat mass and fat-free mass were estimated using the Deurengberg et al. equation [12].More details are presented in the next subsections.

Figure B :
Figure B: Comparison of mean body weight between the Dynamics of Childhood Growth and Obesity Model and mean observed values in ENSANUT 2018 according to nutritional status in children from 6 to 17 years old

Figure C :7
Figure C: Comparison of mean body weight between the Dynamics of Childhood Growth and Obesity Model and mean observed values in ENSANUT 2018 in children from 6 to 17 years old

Table A :
[1]ritional criteria established in the 2014 guidelines* to determine foods and beverages not permitted for consumption in schools[1].§

Table B :
[2]ritional criteria from 2023 reform of the General Education Law to determine foods and beverages that will be banned in schools, based on warning label criteria[2].

Table C :
Model inputs

Table D :
[13]meters for the energy balance equation adapted from Katan et al.[13] [15]F M ref (t) are called fat-free mass and fat mass of reference at time t, respectively, and denote the average or median values of FM y FFM by age, sex, and BMI category (see section 3.2.1 for more details).ηF M = 180 kcal/kg and η F F M = 230 kcal/kg account for "biochemical efficiencies associated to fat and protein synthesis".ρF M = 9400 kcal/kg and ρ F F M = (4.3•F F M ref (t) + 837) kcal/kg are the energy densities for changes in F F M ref (t) and F M ref (t)), respectively.prepresents the proportion of energy from EB ref (t) going to fat-free mass (energy partitioning ratio), estimated using Forbes equation:[15]

Table E :
[12]meters for the growth function g(t) Reference fat-free mass and fat mass We estimated daily reference values of fat-free mass (F F M ref ) and fat mass (F M ref (t)) at a population level, using linear interpolations.First, we estimated median values for fat mass and fat-free mass by age, sex, and BMI category.Fat-free mass and fat mass were estimated for each individual in the sample using Deurengberg et al. equation[12] (7)leFshows the median fat mass and fat-free mass by age, sex and BMI category, obtained with equations (8) and(7).Those median values were estimated using rounded age in years (= round(age in months)/12).The exact age in months was not considered because of the lack of sample in some groups of age, sex, and bmi categories.The median values presented in F were taken as reference values of fat-free mass (F F M ref ) and fat mass (F M ref ) by age, sex and BMI category (calibration).To get daily values of reference, we used linear interpolation between ages assuming that, under no intervention, the individual would remain in the same body mass category during the simulation period (one year).For example, a 6-year-old boy with underweight at the initial time would have F F M ref (age = 6) = 14.6 kg and F M ref

Table F :
Median values of fat mass and fat-free mas estimated using anthropometric data from the Mexican Health and nutrition Survey 2018

Table H :
Studies evaluating interventions in nutrition standards and banning processed foods and beverages inside schools.These studies were selected from the literature to estimate a meta-analytic parameter for the banning effect, based on Micha et al. (2018) meta-analytical analysis.

Table I :
Estimates of energy intake, body weight, BMI, and obesity for the baseline and after one year without intervention (BAU).